GC-308 Heart Disease Prediction And Analysis By Machine Learning

The heart is the most crucial part of the Human body. The organ circulates blood out of the circulatory system’s blood vessels. Any disease or failure of this organ causes death. Heart disease is one of the primary sources of death in the cutting-edge world. There are 2,380 deaths from heart disease each day, based on 2018 data. Also, heart disease causes the highest number of deaths globally, with approximately 18 million people dying yearly, meaning around 31This prediction can be made using Machine Learning techniques. With machine learning. Combining a prediction model with machine learning correctly classified results for heart disease with classification Zero r, Grip (FURIA) classification, Decision tree J48, Classification MLP, MLR (multinomial logistic regression), Bagging, Boosting, stacking classification. J48 has the highest accuracy. As it is described that early detection of heart disease plays vital role in saving individuals life. considering the classification method in machine learning is chosen one for diagnosing heart disease and hence there are good outcomes that are came out. This research was based on 2020 survey conducted by CDC on BRFSS. based on these 8 different machine learning methods we have chosen

Evolutionary computation for financial engineering

Over the years, Evolutionary Computation techniques have been applied to various problems where the solution space is very large and complex, and where the irregularities in the solution space make it difficult to employ conventional optimization procedures to look for the global optimum. Computational Intelligence techniques like Neural Networks, Evolutionary Algorithms etc. have become extremely popular in the financial markets owing to the great promise they hold and also because of the exceptional results produced by them through experiments and studies conducted worldwide. Financial Engineering problems are usually very complex and biologically inspired heuristic algorithms (based on Darwin’s concepts of natural selection and survival of the fittest) have gained significant importance in this area, especially for making decisions and solving optimization problems. The author has studied various aspects of Evolutionary Computation along with their applications to financial problems. To test the effectiveness of one such methodology under Evolutionary Computation (Genetic Algorithms), the author implemented a simple genetic algorithm in MATLAB and also experimented with the various parameters involved in Genetic Algorithms to see the variance in results produced by them.Bachelor of Engineerin

Digital healthcare: The only solution for better healthcare during COVID-19 pandemic?

The huge impact of the COVID-19 pandemic on global healthcare systems has prompted search for novel tools to stem the tide. Attention has turned to the digital health community to provide possible health solutions in this time of unprecedented medical crisis to mitigate the impact of this pandemic. The paper shall focus on how digital solutions can impact healthcare during this pandemic

Bacterial cell wall biogenesis is mediated by SEDS and PBP polymerase families functioning semi-autonomously

Multi-protein complexes organized by cytoskeletal proteins are essential for cell wall biogenesis in most bacteria. Current models of the wall assembly mechanism assume class A penicillin-binding proteins (aPBPs), the targets of penicillin-like drugs, function as the primary cell wall polymerases within these machineries. Here, we use an in vivo cell wall polymerase assay in Escherichia coli combined with measurements of the localization dynamics of synthesis proteins to investigate this hypothesis. We find that aPBP activity is not necessary for glycan polymerization by the cell elongation machinery as is commonly believed. Instead, our results indicate that cell wall synthesis is mediated by two distinct polymerase systems, SEDS-family proteins working within the cytoskeletal machines and aPBP enzymes functioning outside of these complexes. These findings thus necessitate a fundamental change in our conception of the cell wall assembly process in bacteria